GeoQuerySet API Reference

class GeoQuerySet(model=None)

Spatial Lookups

The spatial lookups in this section are available for GeometryField and RasterField.

For an introduction, see the spatial lookups introduction. For an overview of what lookups are compatible with a particular spatial backend, refer to the spatial lookup compatibility table.

Lookups with rasters

All examples in the reference below are given for geometry fields and inputs, but the lookups can be used the same way with rasters on both sides. Whenever a lookup doesn’t support raster input, the input is automatically converted to a geometry where necessary using the ST_Polygon function. See also the introduction to raster lookups.

The database operators used by the lookups can be divided into three categories:

• Native raster support N: the operator accepts rasters natively on both sides of the lookup, and raster input can be mixed with geometry inputs.
• Bilateral raster support B: the operator supports rasters only if both sides of the lookup receive raster inputs. Raster data is automatically converted to geometries for mixed lookups.
• Geometry conversion support C. The lookup does not have native raster support, all raster data is automatically converted to geometries.

The examples below show the SQL equivalent for the lookups in the different types of raster support. The same pattern applies to all spatial lookups.

Case	Lookup	SQL Equivalent
N, B	rast__contains=rst	ST_Contains(rast, rst)
N, B	rast__1__contains=(rst, 2)	ST_Contains(rast, 1, rst, 2)
B, C	rast__contains=geom	ST_Contains(ST_Polygon(rast), geom)
B, C	rast__1__contains=geom	ST_Contains(ST_Polygon(rast, 1), geom)
B, C	poly__contains=rst	ST_Contains(poly, ST_Polygon(rst))
B, C	poly__contains=(rst, 1)	ST_Contains(poly, ST_Polygon(rst, 1))
C	rast__crosses=rst	ST_Crosses(ST_Polygon(rast), ST_Polygon(rst))
C	rast__1__crosses=(rst, 2)	ST_Crosses(ST_Polygon(rast, 1), ST_Polygon(rst, 2))
C	rast__crosses=geom	ST_Crosses(ST_Polygon(rast), geom)
C	poly__crosses=rst	ST_Crosses(poly, ST_Polygon(rst))

Spatial lookups with rasters are only supported for PostGIS backends (denominated as PGRaster in this section).

bbcontains

Availability: PostGIS, MySQL, SpatiaLite, PGRaster (Native)

Tests if the geometry or raster field’s bounding box completely contains the lookup geometry’s bounding box.

Example:

Zipcode.objects.filter(poly__bbcontains=geom)

Backend	SQL Equivalent
PostGIS	poly ~ geom
MySQL	MBRContains(poly, geom)
SpatiaLite	MbrContains(poly, geom)

bboverlaps

Availability: PostGIS, MySQL, SpatiaLite, PGRaster (Native)

Tests if the geometry field’s bounding box overlaps the lookup geometry’s bounding box.

Example:

Zipcode.objects.filter(poly__bboverlaps=geom)

Backend	SQL Equivalent
PostGIS	poly && geom
MySQL	MBROverlaps(poly, geom)
SpatiaLite	MbrOverlaps(poly, geom)

contained

Availability: PostGIS, MySQL, SpatiaLite, PGRaster (Native)

Tests if the geometry field’s bounding box is completely contained by the lookup geometry’s bounding box.

Example:

Zipcode.objects.filter(poly__contained=geom)

Backend	SQL Equivalent
PostGIS	poly @ geom
MySQL	MBRWithin(poly, geom)
SpatiaLite	MbrWithin(poly, geom)

contains

Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)

Tests if the geometry field spatially contains the lookup geometry.

Example:

Zipcode.objects.filter(poly__contains=geom)

Backend	SQL Equivalent
PostGIS	ST_Contains(poly, geom)
Oracle	SDO_CONTAINS(poly, geom)
MySQL	MBRContains(poly, geom)
SpatiaLite	Contains(poly, geom)

contains_properly

Availability: PostGIS, PGRaster (Bilateral)

Returns true if the lookup geometry intersects the interior of the geometry field, but not the boundary (or exterior).

Example:

Zipcode.objects.filter(poly__contains_properly=geom)

Backend	SQL Equivalent
PostGIS	ST_ContainsProperly(poly, geom)

coveredby

Availability: PostGIS, Oracle, PGRaster (Bilateral)

Tests if no point in the geometry field is outside the lookup geometry. [3]

Example:

Zipcode.objects.filter(poly__coveredby=geom)

Backend	SQL Equivalent
PostGIS	ST_CoveredBy(poly, geom)
Oracle	SDO_COVEREDBY(poly, geom)

covers

Availability: PostGIS, Oracle, PGRaster (Bilateral)

Tests if no point in the lookup geometry is outside the geometry field. [3]

Example:

Zipcode.objects.filter(poly__covers=geom)

Backend	SQL Equivalent
PostGIS	ST_Covers(poly, geom)
Oracle	SDO_COVERS(poly, geom)

crosses

Availability: PostGIS, SpatiaLite, PGRaster (Conversion)

Tests if the geometry field spatially crosses the lookup geometry.

Example:

Zipcode.objects.filter(poly__crosses=geom)

Backend	SQL Equivalent
PostGIS	ST_Crosses(poly, geom)
SpatiaLite	Crosses(poly, geom)

disjoint

Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)

Tests if the geometry field is spatially disjoint from the lookup geometry.

Example:

Zipcode.objects.filter(poly__disjoint=geom)

Backend	SQL Equivalent
PostGIS	ST_Disjoint(poly, geom)
Oracle	SDO_GEOM.RELATE(poly, 'DISJOINT', geom, 0.05)
MySQL	MBRDisjoint(poly, geom)
SpatiaLite	Disjoint(poly, geom)

equals

Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Conversion)

exact, same_as

Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)

intersects

Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)

Tests if the geometry field spatially intersects the lookup geometry.

Example:

Zipcode.objects.filter(poly__intersects=geom)

Backend	SQL Equivalent
PostGIS	ST_Intersects(poly, geom)
Oracle	SDO_OVERLAPBDYINTERSECT(poly, geom)
MySQL	MBRIntersects(poly, geom)
SpatiaLite	Intersects(poly, geom)

isvalid

Availability: PostGIS, Oracle, SpatiaLite

Tests if the geometry is valid.

Example:

Zipcode.objects.filter(poly__isvalid=True)

Backend	SQL Equivalent
PostGIS, SpatiaLite	ST_IsValid(poly)
Oracle	SDO_GEOM.VALIDATE_GEOMETRY_WITH_CONTEXT(poly, 0.05) = 'TRUE'

overlaps

Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)

relate

Availability: PostGIS, Oracle, SpatiaLite, PGRaster (Conversion)

Tests if the geometry field is spatially related to the lookup geometry by the values given in the given pattern. This lookup requires a tuple parameter, (geom, pattern); the form of pattern will depend on the spatial backend:

PostGIS & SpatiaLite

On these spatial backends the intersection pattern is a string comprising nine characters, which define intersections between the interior, boundary, and exterior of the geometry field and the lookup geometry. The intersection pattern matrix may only use the following characters: 1, 2, T, F, or *. This lookup type allows users to “fine tune” a specific geometric relationship consistent with the DE-9IM model. [1]

Geometry example:

# A tuple lookup parameter is used to specify the geometry and
# the intersection pattern (the pattern here is for 'contains').
Zipcode.objects.filter(poly__relate=(geom, 'T*T***FF*'))

PostGIS SQL equivalent:

SELECT ... WHERE ST_Relate(poly, geom, 'T*T***FF*')

SpatiaLite SQL equivalent:

SELECT ... WHERE Relate(poly, geom, 'T*T***FF*')

Raster example:

Zipcode.objects.filter(poly__relate=(rast, 1, 'T*T***FF*'))
Zipcode.objects.filter(rast__2__relate=(rast, 1, 'T*T***FF*'))

PostGIS SQL equivalent:

SELECT ... WHERE ST_Relate(poly, ST_Polygon(rast, 1), 'T*T***FF*')
SELECT ... WHERE ST_Relate(ST_Polygon(rast, 2), ST_Polygon(rast, 1), 'T*T***FF*')

Oracle

Here the relation pattern is comprised of at least one of the nine relation strings: TOUCH, OVERLAPBDYDISJOINT, OVERLAPBDYINTERSECT, EQUAL, INSIDE, COVEREDBY, CONTAINS, COVERS, ON, and ANYINTERACT. Multiple strings may be combined with the logical Boolean operator OR, for example, 'inside+touch'. [2] The relation strings are case-insensitive.

Example:

Zipcode.objects.filter(poly__relate=(geom, 'anyinteract'))

Oracle SQL equivalent:

SELECT ... WHERE SDO_RELATE(poly, geom, 'anyinteract')

touches

Availability: PostGIS, Oracle, MySQL, SpatiaLite

Tests if the geometry field spatially touches the lookup geometry.

Example:

Zipcode.objects.filter(poly__touches=geom)

Backend	SQL Equivalent
PostGIS	ST_Touches(poly, geom)
MySQL	MBRTouches(poly, geom)
Oracle	SDO_TOUCH(poly, geom)
SpatiaLite	Touches(poly, geom)

within

Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)

Tests if the geometry field is spatially within the lookup geometry.

Example:

Zipcode.objects.filter(poly__within=geom)

Backend	SQL Equivalent
PostGIS	ST_Within(poly, geom)
MySQL	MBRWithin(poly, geom)
Oracle	SDO_INSIDE(poly, geom)
SpatiaLite	Within(poly, geom)

left

Availability: PostGIS, PGRaster (Conversion)

Tests if the geometry field’s bounding box is strictly to the left of the lookup geometry’s bounding box.

Example:

Zipcode.objects.filter(poly__left=geom)

PostGIS equivalent:

SELECT ... WHERE poly << geom

right

Availability: PostGIS, PGRaster (Conversion)

Tests if the geometry field’s bounding box is strictly to the right of the lookup geometry’s bounding box.

Example:

Zipcode.objects.filter(poly__right=geom)

PostGIS equivalent:

SELECT ... WHERE poly >> geom

overlaps_left

Availability: PostGIS, PGRaster (Bilateral)

Tests if the geometry field’s bounding box overlaps or is to the left of the lookup geometry’s bounding box.

Example:

Zipcode.objects.filter(poly__overlaps_left=geom)

PostGIS equivalent:

SELECT ... WHERE poly &< geom

overlaps_right

Availability: PostGIS, PGRaster (Bilateral)

Tests if the geometry field’s bounding box overlaps or is to the right of the lookup geometry’s bounding box.

Example:

Zipcode.objects.filter(poly__overlaps_right=geom)

PostGIS equivalent:

SELECT ... WHERE poly &> geom

overlaps_above

Availability: PostGIS, PGRaster (Conversion)

Tests if the geometry field’s bounding box overlaps or is above the lookup geometry’s bounding box.

Example:

Zipcode.objects.filter(poly__overlaps_above=geom)

PostGIS equivalent:

SELECT ... WHERE poly |&> geom

overlaps_below

Availability: PostGIS, PGRaster (Conversion)

Tests if the geometry field’s bounding box overlaps or is below the lookup geometry’s bounding box.

Example:

Zipcode.objects.filter(poly__overlaps_below=geom)

PostGIS equivalent:

SELECT ... WHERE poly &<| geom

strictly_above

Availability: PostGIS, PGRaster (Conversion)

Tests if the geometry field’s bounding box is strictly above the lookup geometry’s bounding box.

Example:

Zipcode.objects.filter(poly__strictly_above=geom)

PostGIS equivalent:

SELECT ... WHERE poly |>> geom

strictly_below

Availability: PostGIS, PGRaster (Conversion)

Tests if the geometry field’s bounding box is strictly below the lookup geometry’s bounding box.

Example:

Zipcode.objects.filter(poly__strictly_below=geom)

PostGIS equivalent:

SELECT ... WHERE poly <<| geom

Distance Lookups

Availability: PostGIS, Oracle, SpatiaLite, PGRaster (Native)

For an overview on performing distance queries, please refer to the distance queries introduction.

Distance lookups take the following form:

<field>__<distance lookup>=(<geometry/raster>, <distance value>[, 'spheroid'])
<field>__<distance lookup>=(<raster>, <band_index>, <distance value>[, 'spheroid'])
<field>__<band_index>__<distance lookup>=(<raster>, <band_index>, <distance value>[, 'spheroid'])

The value passed into a distance lookup is a tuple; the first two values are mandatory, and are the geometry to calculate distances to, and a distance value (either a number in units of the field, a Distance object, or a query expression <ref/models/expressions>). To pass a band index to the lookup, use a 3-tuple where the second entry is the band index.

On every distance lookup except dwithin, an optional element, 'spheroid', may be included to use the more accurate spheroid distance calculation functions on fields with a geodetic coordinate system.

On PostgreSQL, the 'spheroid' option uses ST_DistanceSpheroid instead of ST_DistanceSphere. The simpler ST_Distance function is used with projected coordinate systems. Rasters are converted to geometries for spheroid based lookups.

distance_gt

Returns models where the distance to the geometry field from the lookup geometry is greater than the given distance value.

Example:

Zipcode.objects.filter(poly__distance_gt=(geom, D(m=5)))

Backend	SQL Equivalent
PostGIS	ST_Distance/ST_Distance_Sphere(poly, geom) > 5
Oracle	SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) > 5
SpatiaLite	Distance(poly, geom) > 5

distance_gte

Returns models where the distance to the geometry field from the lookup geometry is greater than or equal to the given distance value.

Example:

Zipcode.objects.filter(poly__distance_gte=(geom, D(m=5)))

Backend	SQL Equivalent
PostGIS	ST_Distance/ST_Distance_Sphere(poly, geom) >= 5
Oracle	SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) >= 5
SpatiaLite	Distance(poly, geom) >= 5

distance_lt

Returns models where the distance to the geometry field from the lookup geometry is less than the given distance value.

Example:

Zipcode.objects.filter(poly__distance_lt=(geom, D(m=5)))

Backend	SQL Equivalent
PostGIS	ST_Distance/ST_Distance_Sphere(poly, geom) < 5
Oracle	SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) < 5
SpatiaLite	Distance(poly, geom) < 5

distance_lte

Returns models where the distance to the geometry field from the lookup geometry is less than or equal to the given distance value.

Example:

Zipcode.objects.filter(poly__distance_lte=(geom, D(m=5)))

Backend	SQL Equivalent
PostGIS	ST_Distance/ST_Distance_Sphere(poly, geom) <= 5
Oracle	SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) <= 5
SpatiaLite	Distance(poly, geom) <= 5

dwithin

Returns models where the distance to the geometry field from the lookup geometry are within the given distance from one another. Note that you can only provide Distance objects if the targeted geometries are in a projected system. For geographic geometries, you should use units of the geometry field (e.g. degrees for WGS84) .

Example:

Zipcode.objects.filter(poly__dwithin=(geom, D(m=5)))

Backend	SQL Equivalent
PostGIS	ST_DWithin(poly, geom, 5)
Oracle	SDO_WITHIN_DISTANCE(poly, geom, 5)
SpatiaLite	PtDistWithin(poly, geom, 5)

GeoQuerySet Methods

GeoQuerySet methods specify that a spatial operation be performed on each spatial operation on each geographic field in the queryset and store its output in a new attribute on the model (which is generally the name of the GeoQuerySet method).

There are also aggregate GeoQuerySet methods which return a single value instead of a queryset. This section will describe the API and availability of every GeoQuerySet method available in GeoDjango.

With a few exceptions, the following keyword arguments may be used with all GeoQuerySet methods:

Keyword Argument	Description
field_name	By default, GeoQuerySet methods use the first geographic field encountered in the model. This keyword should be used to specify another geographic field (e.g., field_name='point2') when there are multiple geographic fields in a model. On PostGIS, the field_name keyword may also be used on geometry fields in models that are related via a ForeignKey relation (e.g., field_name='related__point').
model_att	By default, GeoQuerySet methods typically attach their output in an attribute with the same name as the GeoQuerySet method. Setting this keyword with the desired attribute name will override this default behavior. For example, qs = Zipcode.objects.centroid(model_att='c') will attach the centroid of the Zipcode geometry field in a c attribute on every model rather than in a centroid attribute. This keyword is required if a method name clashes with an existing GeoQuerySet method – if you wanted to use the area() method on model with a PolygonField named area, for example.

Measurement

Availability: PostGIS, Oracle, SpatiaLite

area

GeoQuerySet.area(**kwargs)

Returns the area of the geographic field in an area attribute on each element of this GeoQuerySet.

distance

GeoQuerySet.distance(geom, **kwargs)

This method takes a geometry as a parameter, and attaches a distance attribute to every model in the returned queryset that contains the distance (as a Distance object) to the given geometry.

In the following example (taken from the GeoDjango distance tests), the distance from the Tasmanian city of Hobart to every other PointField in the AustraliaCity queryset is calculated:

>>> pnt = AustraliaCity.objects.get(name='Hobart').point
>>> for city in AustraliaCity.objects.distance(pnt): print(city.name, city.distance)
Wollongong 990071.220408 m
Shellharbour 972804.613941 m
Thirroul 1002334.36351 m
Mittagong 975691.632637 m
Batemans Bay 834342.185561 m
Canberra 598140.268959 m
Melbourne 575337.765042 m
Sydney 1056978.87363 m
Hobart 0.0 m
Adelaide 1162031.83522 m
Hillsdale 1049200.46122 m

length

GeoQuerySet.length(**kwargs)

Returns the length of the geometry field in a length attribute (a Distance object) on each model in the queryset.

perimeter

GeoQuerySet.perimeter(**kwargs)

Returns the perimeter of the geometry field in a perimeter attribute (a Distance object) on each model in the queryset.

Geometry Relationships

The following methods take no arguments, and attach geometry objects each element of the GeoQuerySet that is the result of relationship function evaluated on the geometry field.

centroid

GeoQuerySet.centroid(**kwargs)

Availability: PostGIS, Oracle, SpatiaLite

Returns the centroid value for the geographic field in a centroid attribute on each element of the GeoQuerySet.

envelope

GeoQuerySet.envelope(**kwargs)

Availability: PostGIS, SpatiaLite

Returns a geometry representing the bounding box of the geometry field in an envelope attribute on each element of the GeoQuerySet.

point_on_surface

GeoQuerySet.point_on_surface(**kwargs)

Availability: PostGIS, Oracle, SpatiaLite

Returns a Point geometry guaranteed to lie on the surface of the geometry field in a point_on_surface attribute on each element of the queryset; otherwise sets with None.

Geometry Editors

force_rhr

GeoQuerySet.force_rhr(**kwargs)

Availability: PostGIS

Returns a modified version of the polygon/multipolygon in which all of the vertices follow the Right-Hand-Rule, and attaches as a force_rhr attribute on each element of the queryset.

reverse_geom

GeoQuerySet.reverse_geom(**kwargs)

Availability: PostGIS, Oracle

Reverse the coordinate order of the geometry field, and attaches as a reverse attribute on each element of the queryset.

scale

GeoQuerySet.scale(x, y, z=0.0, **kwargs)

Availability: PostGIS, SpatiaLite

snap_to_grid

GeoQuerySet.snap_to_grid(*args, **kwargs)

Snap all points of the input geometry to the grid. How the geometry is snapped to the grid depends on how many numeric (either float, integer, or long) arguments are given.

Number of Arguments	Description
1	A single size to snap bot the X and Y grids to.
2	X and Y sizes to snap the grid to.
4	X, Y sizes and the corresponding X, Y origins.

transform

GeoQuerySet.transform(srid=4326, **kwargs)

Availability: PostGIS, Oracle, SpatiaLite

The transform method transforms the geometry field of a model to the spatial reference system specified by the srid parameter. If no srid is given, then 4326 (WGS84) is used by default.

Example:

>>> qs = Zipcode.objects.all().transform() # Transforms to WGS84
>>> qs = Zipcode.objects.all().transform(32140) # Transforming to "NAD83 / Texas South Central"
>>> print(qs[0].poly.srid)
32140
>>> print(qs[0].poly)
POLYGON ((234055.1698884720099159 4937796.9232223574072123 ...

translate

GeoQuerySet.translate(x, y, z=0.0, **kwargs)

Availability: PostGIS, SpatiaLite

Translates the geometry field to a new location using the given numeric parameters as offsets.

Geometry Operations

Availability: PostGIS, Oracle, SpatiaLite

The following methods all take a geometry as a parameter and attach a geometry to each element of the GeoQuerySet that is the result of the operation.

difference

GeoQuerySet.difference(geom)

Returns the spatial difference of the geographic field with the given geometry in a difference attribute on each element of the GeoQuerySet.

intersection

GeoQuerySet.intersection(geom)

Returns the spatial intersection of the geographic field with the given geometry in an intersection attribute on each element of the GeoQuerySet.

sym_difference

GeoQuerySet.sym_difference(geom)

Returns the symmetric difference of the geographic field with the given geometry in a sym_difference attribute on each element of the GeoQuerySet.

union

GeoQuerySet.union(geom)

Returns the union of the geographic field with the given geometry in an union attribute on each element of the GeoQuerySet.

Geometry Output

The following GeoQuerySet methods will return an attribute that has the value of the geometry field in each model converted to the requested output format.

geohash

GeoQuerySet.geohash(precision=20, **kwargs)

Attaches a geohash attribute to every model the queryset containing the GeoHash representation of the geometry.

geojson

GeoQuerySet.geojson(**kwargs)

Availability: PostGIS, SpatiaLite

Attaches a geojson attribute to every model in the queryset that contains the GeoJSON representation of the geometry.

Keyword Argument	Description
precision	It may be used to specify the number of significant digits for the coordinates in the GeoJSON representation – the default value is 8.
crs	Set this to True if you want the coordinate reference system to be included in the returned GeoJSON.
bbox	Set this to True if you want the bounding box to be included in the returned GeoJSON.

gml

GeoQuerySet.gml(**kwargs)

Availability: PostGIS, Oracle, SpatiaLite

Attaches a gml attribute to every model in the queryset that contains the Geographic Markup Language (GML) representation of the geometry.

Example:

>>> qs = Zipcode.objects.all().gml()
>>> print(qs[0].gml)
<gml:Polygon srsName="EPSG:4326"><gml:OuterBoundaryIs>-147.78711,70.245363 ...  -147.78711,70.245363</gml:OuterBoundaryIs></gml:Polygon>

Keyword Argument	Description
precision	This keyword is for PostGIS only. It may be used to specify the number of significant digits for the coordinates in the GML representation – the default value is 8.
version	This keyword is for PostGIS only. It may be used to specify the GML version used, and may only be values of 2 or 3. The default value is 2.

kml

GeoQuerySet.kml(**kwargs)

Availability: PostGIS, SpatiaLite

Attaches a kml attribute to every model in the queryset that contains the Keyhole Markup Language (KML) representation of the geometry fields. It should be noted that the contents of the KML are transformed to WGS84 if necessary.

Example:

>>> qs = Zipcode.objects.all().kml()
>>> print(qs[0].kml)
<Polygon><outerBoundaryIs><LinearRing><coordinates>-103.04135,36.217596,0 ... -103.04135,36.217596,0</coordinates></LinearRing></outerBoundaryIs></Polygon>

Keyword Argument	Description
precision	This keyword may be used to specify the number of significant digits for the coordinates in the KML representation – the default value is 8.

svg

GeoQuerySet.svg(**kwargs)

Availability: PostGIS, SpatiaLite

Attaches a svg attribute to every model in the queryset that contains the Scalable Vector Graphics (SVG) path data of the geometry fields.

Keyword Argument	Description
relative	If set to True, the path data will be implemented in terms of relative moves. Defaults to False, meaning that absolute moves are used instead.
precision	This keyword may be used to specify the number of significant digits for the coordinates in the SVG representation – the default value is 8.

Miscellaneous

mem_size

GeoQuerySet.mem_size(**kwargs)

Availability: PostGIS

Returns the memory size (number of bytes) that the geometry field takes in a mem_size attribute on each element of the GeoQuerySet.

num_geom

GeoQuerySet.num_geom(**kwargs)

Availability: PostGIS, Oracle, SpatiaLite

Returns the number of geometries in a num_geom attribute on each element of the GeoQuerySet if the geometry field is a collection (e.g., a GEOMETRYCOLLECTION or MULTI* field); otherwise sets with None.

num_points

GeoQuerySet.num_points(**kwargs)

Availability: PostGIS, Oracle, SpatiaLite

Returns the number of points in the first linestring in the geometry field in a num_points attribute on each element of the GeoQuerySet; otherwise sets with None.

Aggregate Functions

Django provides some GIS-specific aggregate functions. For details on how to use these aggregate functions, see the topic guide on aggregation.

Keyword Argument	Description
tolerance	This keyword is for Oracle only. It is for the tolerance value used by the SDOAGGRTYPE procedure; the Oracle documentation has more details.

Example:

>>> from django.contrib.gis.db.models import Extent, Union
>>> WorldBorder.objects.aggregate(Extent('mpoly'), Union('mpoly'))

Collect

class Collect(geo_field)

Availability: PostGIS, SpatiaLite

Returns a GEOMETRYCOLLECTION or a MULTI geometry object from the geometry column. This is analogous to a simplified version of the Union aggregate, except it can be several orders of magnitude faster than performing a union because it simply rolls up geometries into a collection or multi object, not caring about dissolving boundaries.

Extent

class Extent(geo_field)

Availability: PostGIS, Oracle, SpatiaLite

Returns the extent of all geo_field in the QuerySet as a four-tuple, comprising the lower left coordinate and the upper right coordinate.

Example:

>>> qs = City.objects.filter(name__in=('Houston', 'Dallas')).aggregate(Extent('poly'))
>>> print(qs['poly__extent'])
(-96.8016128540039, 29.7633724212646, -95.3631439208984, 32.782058715820)

Extent3D

class Extent3D(geo_field)

Availability: PostGIS

Returns the 3D extent of all geo_field in the QuerySet as a six-tuple, comprising the lower left coordinate and upper right coordinate (each with x, y, and z coordinates).

Example:

>>> qs = City.objects.filter(name__in=('Houston', 'Dallas')).aggregate(Extent3D('poly'))
>>> print(qs['poly__extent3d'])
(-96.8016128540039, 29.7633724212646, 0, -95.3631439208984, 32.782058715820, 0)

MakeLine

class MakeLine(geo_field)

Availability: PostGIS, SpatiaLite

Returns a LineString constructed from the point field geometries in the QuerySet. Currently, ordering the queryset has no effect.

Example:

>>> qs = City.objects.filter(name__in=('Houston', 'Dallas')).aggregate(MakeLine('poly'))
>>> print(qs['poly__makeline'])
LINESTRING (-95.3631510000000020 29.7633739999999989, -96.8016109999999941 32.7820570000000018)

Union

class Union(geo_field)

Availability: PostGIS, Oracle, SpatiaLite

This method returns a GEOSGeometry object comprising the union of every geometry in the queryset. Please note that use of Union is processor intensive and may take a significant amount of time on large querysets.

Example:

>>> u = Zipcode.objects.aggregate(Union(poly))  # This may take a long time.
>>> u = Zipcode.objects.filter(poly__within=bbox).aggregate(Union(poly))  # A more sensible approach.

Footnotes

[1]	See OpenGIS Simple Feature Specification For SQL, at Ch. 2.1.13.2, p. 2-13 (The Dimensionally Extended Nine-Intersection Model).

[2]	See SDO_RELATE documentation, from the Oracle Spatial and Graph Developer’s Guide.

[3]	(1, 2) For an explanation of this routine, read Quirks of the “Contains” Spatial Predicate by Martin Davis (a PostGIS developer).